2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS最新文献_第8页

Sar Amplitude Exploitation for Systematic Landslide Failure Detection 基于Sar振幅的滑坡破坏系统检测

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Pub Date : 2021-07-11 DOI: 10.1109/IGARSS47720.2021.9553991

A. Mondini

引用次数: 1

Development of a Long-Term Dataset of China Surface Urban Heat Island for Policy Making: Spatio-Temporal Characteristics 面向政策制定的中国地表城市热岛长期数据集构建:时空特征

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Pub Date : 2021-07-11 DOI: 10.1109/IGARSS47720.2021.9554127

Lu Niu, Zhong Peng, R. Tang, Zhengfeng Zhang

引用次数: 4

Exploring the Transmission of VNIR Light Through Martian Regolith 探索近红外光通过火星风化层的传输

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Pub Date : 2021-07-11 DOI: 10.1109/IGARSS47720.2021.9554798

G. Baranoski, Mark Iwanchyshyn, B. Kimmel, Petri Varsa, Spencer R. Van Leeuwen

{"title":"Exploring the Transmission of VNIR Light Through Martian Regolith","authors":"G. Baranoski, Mark Iwanchyshyn, B. Kimmel, Petri Varsa, Spencer R. Van Leeuwen","doi":"10.1109/IGARSS47720.2021.9554798","DOIUrl":"https://doi.org/10.1109/IGARSS47720.2021.9554798","url":null,"abstract":"The identification and analysis of hyperspectral visible and near-infrared signatures of key targets, notably silica-rich outcrops, on Mars can be considerably affected by the presence of covering regolith materials. Before reaching and after being reflected by these targets, the impinging electromagnetic radiation is propagated through the regolith materials. Hence, the investigation of these materials' light transmission capabilities, the focal point of this work, can be instrumental for the correct interpretation of the hyperspectral responses of silica-rich deposits and other subsurface targets. In the absence of actual Martian regolith samples to be used in transmittance experiments, high-fidelity modeling approaches can effectively contribute to advance the knowledge in this area. Accordingly, we carried out a controlled assessment of the quantitative and qualitative traits of light transmitted through representative samples of Martian regolith using a first-principles simulation framework supported by radiometric data acquired in the Gusev crater on Mars. We also examined changes in the light transmission profiles of Martian regoliths caused by environmentally-induced variations in their grains' morphology.","PeriodicalId":315312,"journal":{"name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128258383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Comparative Study of Noise Sensitivity on Different Hyperspectral Classification Methods 不同高光谱分类方法的噪声敏感性比较研究

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Pub Date : 2021-07-11 DOI: 10.1109/IGARSS47720.2021.9554168

Congyu Li, Xinxin Liu, Xudong Kang, Shutao Li

引用次数: 0

A Ku-Band Airborne InSAR for Snow Characterization at Trail Valley Creek 一种用于Trail Valley Creek积雪特征的ku波段机载InSAR

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Pub Date : 2021-07-11 DOI: 10.1109/IGARSS47720.2021.9554888

P. Siqueira, M. Adam, S. Kraatz, D. Lagoy, M. Torres, L. Tsang, Jiyue Zhu, C. Derksen, J. King

引用次数: 2

A Penalization-Based NMF Approach for Hyperspectral Unmixing Addressing Spectral Variability with an Additively-Tuned Mixing Model 一种基于惩罚的高光谱解混方法，利用加性调谐混合模型处理光谱变异性

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Pub Date : 2021-07-11 DOI: 10.1109/IGARSS47720.2021.9553366

S. Brezini, Y. Deville, M. S. Karoui, Fatima Zohra Benhalouche, A. Ouamri

{"title":"A Penalization-Based NMF Approach for Hyperspectral Unmixing Addressing Spectral Variability with an Additively-Tuned Mixing Model","authors":"S. Brezini, Y. Deville, M. S. Karoui, Fatima Zohra Benhalouche, A. Ouamri","doi":"10.1109/IGARSS47720.2021.9553366","DOIUrl":"https://doi.org/10.1109/IGARSS47720.2021.9553366","url":null,"abstract":"Remote sensing hyperspectral sensors are often limited in their spatial resolutions, which leads to mixed pixels. The linear spectral unmixing process is frequently used to extract endmember spectra and their abundance fractions. The standard linear mixing model considers that each endmember is represented by the same spectral signature in the entire image. However, such a basic hypothesis is not relevant in most practical situations since the spectral signature of an endmember can spatially vary. This intra-class variability phenomenon can be considered by introducing the concept of classes of endmembers. Recently, a structured additively-tuned linear mixing model, with its constraints, was proposed, with an associated unmixing method, to address this phenomenon. That method, based on Nonnegative Matrix Factorization (NMF), optimizes a cost function with iterative and multiplicative update rules supplemented by additional constraints that control the spectral variability. In the present work, two penalization terms that more efficiently manage the spectral variability are added to the considered cost function, for the same structured mixing model, and new NMF-based iterative and multiplicative update rules are deduced for achieving the unmixing process taking the considered phenomenon into account. The proposed algorithm proves to be very attractive as clearly reported by conducted experiments based on synthetic data.","PeriodicalId":315312,"journal":{"name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128731100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Classification of Multi-Channel SAR Data Based on MB-U2-ACNet Model for Shanghai Nanhui Dongtan Intertidal Zone Environment Monitoring 基于MB-U2-ACNet模型的上海南汇东滩潮间带环境监测多通道SAR数据分类

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Pub Date : 2021-07-11 DOI: 10.1109/IGARSS47720.2021.9555172

Guangyang Liu, B. Liu, Xiaofeng Li, G. Zheng

引用次数: 2

Updates to Good Practices for Estimating Area and Assessing Accuracy of Land Cover and Land Cover Change Products 土地覆盖和土地覆盖变化产品面积估算和准确性评估良好规范的更新

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Pub Date : 2021-07-11 DOI: 10.1109/IGARSS47720.2021.9554475

P. Olofsson

{"title":"Updates to Good Practices for Estimating Area and Assessing Accuracy of Land Cover and Land Cover Change Products","authors":"P. Olofsson","doi":"10.1109/IGARSS47720.2021.9554475","DOIUrl":"https://doi.org/10.1109/IGARSS47720.2021.9554475","url":null,"abstract":"While satellites have been collecting data since the 1970s, the remote sensing technology has exploded over the last decade, with the number of remote sensing instruments being far greater than ever before. Easy access to powerful computing platforms that give users direct access to the vast archives of satellite data, have created a situation where making maps and other spatial datasets has never been easier. This development is welcomed and gives geographical sciences an unprecedented potential to contribute to decision-making and policy. However, mapping complex and often spatially continuous surface conditions into a set of discrete map categories is bound to result in some of the map units being erroneous. The magnitude of errors will determine the reliability, usage, and interpretation of the map, which is why map users and producers have a direct interest in communicating and understanding the quality of maps. The quality of maps has traditionally been communicated via a so-called accuracy assessment, which results in measures of map accuracy based on the comparison of the map and a sample of observations of reference conditions on the land surface. While accuracy assessments are important and valuable, an analysis that ends with measures of map accuracy -- being it overall map accuracy or class-specific -- merely shows that the map is more or less incorrect (the very unlikely event of achieving 100% accuracy excluded). In policy and decision-making context, remote sensing is often used to quantify various phenomena on the land surface, such as the area of deforestation or urban expansion; but the presence of errors in remote sensing-based maps prevents the estimation of area directly from the map (“pixel counting”). As stated in the GFOI Methods & Guidance Document [1]:","PeriodicalId":315312,"journal":{"name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128984288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Non-Gaussian Extensions for the Detection of Persistent Scatterers: Addressing the Limitations of Gaussian Models for InSAR Imagery 持续散射体检测的非高斯扩展:解决InSAR图像高斯模型的局限性

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Pub Date : 2021-07-11 DOI: 10.1109/IGARSS47720.2021.9553184

Stacey A. Huang, H. Zebker

{"title":"Non-Gaussian Extensions for the Detection of Persistent Scatterers: Addressing the Limitations of Gaussian Models for InSAR Imagery","authors":"Stacey A. Huang, H. Zebker","doi":"10.1109/IGARSS47720.2021.9553184","DOIUrl":"https://doi.org/10.1109/IGARSS47720.2021.9553184","url":null,"abstract":"It is well-known that the backscatter of high-resolution Synthetic Aperture Radar (SAR) imagery is non-Gaussian in nature. As a result, corresponding heavy-tailed models have been successfully incorporated for the design of improved SAR target detectors. However, Gaussian-based detectors are largely still applied for selection of persistent scatterers (PS) in Interferometric Synthetic Aperture Radar (InSAR) imagery, and implications for the performance of PS techniques have not been well-studied. Here, we extend an existing Gaussian model for PS to incorporate non-Gaussian behavior. We then implement the model for PS detection and compare its performance to its Gaussian counterpart, finding that the non-Gaussian model finds a slightly denser network of PS. Further work will focus on analyzing the characteristics of this disparity, including its relationship with terrain and system parameters such as wavelength and bandwidth, and compare the estimated deformation from the non-Gaussian detector compared to an existing Gaussian-based model. Understanding the limitations of Gaussian models will inform the design of improved PS detectors to produce more complete deformation maps and enable the broader application of InSAR for challenging applications, such as observing small strain rates in natural terrain.","PeriodicalId":315312,"journal":{"name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129046299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Land Deformation at Longyao Ground Fissure and Its Surroundings Revealed by Time Series Insar 时间序列Insar揭示的龙瑶地裂缝及其周边地表变形

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Pub Date : 2021-07-11 DOI: 10.1109/IGARSS47720.2021.9554906

Hongyu Liu, Bofeng Li

引用次数: 0